Communications of the ACM
Trust-inspiring explanation interfaces for recommender systems
Knowledge-Based Systems
Eye-tracking product recommenders' usage
Proceedings of the fourth ACM conference on Recommender systems
Consumer decision patterns through eye gaze analysis
Proceedings of the 2010 workshop on Eye gaze in intelligent human machine interaction
Users' (Dis)satisfaction with the personalTV application: Combining objective and subjective data
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
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Online stores offer an increasingly large set of products. Interactive decision aids are becoming indispensable tools assisting users as they search for an ideal product to purchase. For an e-commerce website, adopting the correct tools can affect its survival: effective product recommender tools are increasingly recognized by online stores as effective means to sell more products; on the other hand, sites that do not employ intelligent tools will not only see poor purchase volumes but also experience less traffic because consumers are more likely to return to a site employing recommender systems. This paper presents ongoing research in understanding the impact of various decision aids on users' interaction behaviors and their subjective perceptions of these aids. In the current experiment, we employed an eye tracker in an in-depth user study to understand the influence of recommenders on how users select items for the basket set. We collected more than 20,300 fixation data points in 3,648 areas of interest. Our studies show that while users still rely on product filtering tools, the use of recommenders is becoming more prominent in helping them construct the basket set and is monotonically increasing as time goes on.